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A massively parallel algorithm based on DNA computations for constructing minimal spanning trees

Authors: Chin Ching Chiu; Yi-Shiung Yeh;

A massively parallel algorithm based on DNA computations for constructing minimal spanning trees

Abstract

Abstract Although much work has been done on constructing minimal spanning trees, no studies have attempted to solve this problem using DNA computation. This paper describes the first DNA algorithm for constructing minimal spanning trees. In 1994, Leonard M. Adleamn used biological experiments with DNA strands to solve computation problems. The potential benefits of using this particular molecule are enormous due to the massive inherent parallelism of performing concurrent operations on trillions of strands. The proposed algorithm will randomly generate all possible solutions to the problem at hand and isolate the correct solution through repeated separations of the DNA into incorrect solutions and potentially good solutions. This algorithm is simpler than convention algorithms in many aspects such as no requirement for checking the processing elements concurrently, asynchronously, infinite loop, deadlock etc.

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
0
Average
Average
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